Vacuum Cleaner Floor-Type Detection Using Trimmed Torque Estimator
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Solution Overview
Problem
Existing vacuum cleaners, particularly cordless models, face challenges in accurately identifying different flooring types to optimize suction power and cleaning performance, as current methods are prone to inaccuracies and product-specific variations.
Innovation Solution
A computer-implemented method using a trimmed estimator to analyze torque load data from the vacuum cleaner's brush motor, distinguishing between soft and hard flooring categories by processing sensor data to generate a scale parameter that is robust against outliers, allowing precise categorization based on torque variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current sensing methods are used to identify floor type, then floor type detection is achieved, but measurement precision deteriorates due to product-specific variations and noise sensitivity
Solution Approach 1:
The patent transforms the detection parameter from raw current values to statistical characteristics (standard deviation, skewness, kurtosis) of current fluctuations. This parameter transformation makes the detection more robust to product-specific variations and noise, as statistical properties capture the essential patterns of brush motor behavior across different floor types while being invariant to absolute current levels that vary between products.
Solution Approach 2:
The patent introduces statistical analysis as an intermediary layer between the raw current sensor data and the floor type classification. By computing statistical characteristics (standard deviation, skewness, kurtosis) as intermediate features, the system bridges the gap between noisy raw measurements and reliable floor type identification, filtering out product-specific variations while preserving floor-type-discriminative information.
2Productivity
If suction power is increased to improve cleaning performance on soft floors, then dust pick-up improves, but energy consumption increases reducing battery runtime
Solution Approach 1:
The patent implements dynamic adjustment of suction power based on real-time floor type detection. The system continuously monitors brush motor current characteristics, identifies the current floor type using statistical analysis, and dynamically adjusts the suction power accordingly. This dynamic adaptation allows the vacuum to operate at optimal power levels for each floor type, maximizing cleaning performance while minimizing energy consumption.
Solution Approach 2:
The patent establishes a feedback loop where the brush motor current is continuously measured, statistical characteristics are computed, floor type is identified, and suction power is adjusted based on this identification. This closed-loop feedback system ensures that the vacuum cleaner automatically adapts its power consumption to the cleaning requirements of the current floor type, improving overall energy efficiency.
Data Source
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AI summary
A method (600) and system for determining on which of a plurality of categories of flooring, each having a different hardness, a nozzle (111) of a vacuum cleaner (110) is positioned. Data representative of a torque load of a motor that rotates a brush in the nozzle is obtained and processed to generate a trimmed estimator of a parameter that measures variation in the data. A determination that the nozzle is positioned on the softest category of flooring is made in response to the trimmed estimator (620) breaching a predetermined threshold.